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Bayesian Modeling Coherenced Green Synthesis of NiO Nanoparticles Using Camellia sinensis for Efficient Antimicrobial Activity

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Abstract

Among various nanoparticles reported, nickel has been notable for its antimicrobial and photocatalytic exercises. However, to reduce the toxicity of the direct use of nickel, Camellia sinensis (tea) plant extract has been used in this work for the synthesis of nickel oxide nanoparticles (NiO NPs). The synthesis of NiO NPs has been confirmed by the UV absorption peak at 346 nm and photoluminescence peak at 341 nm. TEM images confirm the formation of NiO NPs with an average particle size of 2 nm. SEM pictures are indicating the formation of well-defined nanosheet-like NiO NPs. Statistical tools could be used to reinforce the confidence that the materials have been characterized correctly. Here, the bivariate Gaussian model has been applied to interrelate among absorbance and intensity with the wavelength, which was obtained in UV-Vis and photoluminescence spectra, respectively. A more generalized Bayesian estimate along with 95% highest probability density interval of the maximum absorption or emission wavelength observed at the highest absorbance or intensity has been calculated and investigated by using the observed values through Markov chain Monte Carlo simulations. Further, NiO NPs show efficient antimicrobial activity against both gram-negative and gram-positive bacteria strain. The synthesized NiO NPs using tea leaf extract could provide a green pathway against bacterial pathogens.

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Acknowledgements

The authors are thankful to CSIR-NEIST and Gauhati University for providing the analytical facilities. The authors would like to thank anonymous reviewers and the editorial team for their valuable comments and suggestions that improvised the quality of this article.

Funding Statement

Funding was provided by the Ministry of Human Resource Development, Govt. of India, under TEQIP III.

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Authors and Affiliations

  1. Department of Applied Sciences (Chemical Science Division), Gauhati University, Guwahati, Assam, 781014, India

    Chinmoy Kalita & Pranjal Saikia

  2. Department of Biotechnology, Gauhati University, Guwahati, Assam, 781014, India

    Rajesh Dev Sarkar & Mohan Chandra Kalita

  3. Department of Statistics, Assam University, Silchar, Assam, 788011, India

    Vivek Verma

  4. Department of Chemistry, Pragjyotish College, Guwahati, Assam, 781012, India

    Saitanya Kumar Bharadwaj

  5. Advanced Materials Group, Materials Sciences and Technology Division, CSIR-North East Institute of Science and Technology, Jorhat, 785006, India

    Purna Kanta Boruah & Manash Ranjan Das

  6. Academy of Scientific and Innovative Research, CSIR-NEIST Jorhat Campus, Jorhat, India

    Purna Kanta Boruah & Manash Ranjan Das

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  1. Chinmoy Kalita
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Supplementary Data SEM images, UV-Vis spectra, and PL spectra of NiO NPs (Fig. S1, S2a, and S2b, respectively) are provided as supplementary information.(DOCX 485 kb)

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Kalita, C., Sarkar, R.D., Verma, V. et al. Bayesian Modeling Coherenced Green Synthesis of NiO Nanoparticles Using Camellia sinensis for Efficient Antimicrobial Activity. BioNanoSci. 11, 825–837 (2021). https://doi.org/10.1007/s12668-021-00882-x

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